Page History

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• peter antley 

• Eric Lowe 
• Dale Harris 
• Mike Nurse
• Jenny Tornquist
• Wanchin Chou
• Andy Case
• Reggie Scarpa
• Ash Naik 
• Ken Sayers 
• Bourjali Hi
• Kristin McDonald 
• Susan Chudwick 
• James Madison 
• Jefferson Braswell 
• Nathan Southern 
• George Bradner 

Goals

Meeting Minutes

I. Opening

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II. Agenda - Data Modeling and Internal Data Work - Mr. Antley

Mr. Antley pulled up dialogue - graphic on earned premium - Greg W. spoke about car years last week

Mr. Antley: we want to discuss concept of business layer

Stat data as it is gives us what we need to do regulatory reporting. Specified accounting date and duration - clarification of coverages and exposures. 

When we consider requests brought to us, some terms are brought up repeatedly: EP, incurred premium, exposures and premiums incurred and written, average expenditures and premiums, loss ratios, underwriting expenses, etc. 

Today: we take input records and process those records and calculate all of these categories (various figures) on a quarterly basis. In current mode, grouped by policy and by quarter. Select queries feasible - yield year outputs. Calculations = aggregations.

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A. Overview/Recap

1. Discussion of data modeling and what idl project is doing with data. Concerned that discussions may be becoming overly technical. Wants to dial the tech speak down a bit
2. Pulled up graphic on Earned Premium - 3 columns: Input / Business Layer /Output
3. Noted that last week, Mr. Williams led a discussion on car years. 
4. Also noted that he led the discussion on business layer - wants to revisit and continue this.

B. Business Layer

1. Re: Input, Stat plan as it is gives us adequate data to do regulatory reporting, and we can ingest most of needed information:
   1. Accounting date
   2. Duration
   3. Coverages and exposures
2. Re: Output: some of the terms for which people are asking (presented examples here): e..g, Earned premiums, car years, incurred loss, earned/written exposures and premiums, incurred claims/losses, calculated ratios, average expenditures, average premiums, underwriting expenses.
3. Mr. Antley: the way they solve (@AAIS, in his warehouse) these questions today: they take the input records, process these to be centered around the idea of a policy, and then calculate: earned premium, paid loss, incurred loss, outstanding losses, earned exposures, paid claim counts, outstanding claim counts. They calculate all of this on quarterly basis. Sits and persists in data store on level on which they are making reports, they have these terms, grouped by policy, calculated by quarter. If x person asks "what is my earned premium for the year, for these kinds of coverages," he does a select query that does filters and aggregates and produces year output. Data on a policy and quarterly basis with the premium after it has been earned.
4. In AWG: Discussion - how do we set up HDS so it is accessible to regulators, sans putting undue burden on rest of system

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1. ?
2. Pointed to base layer, from which we

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1. answering questions. How do we make it accessible to

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1. the persons making queries?

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1. Quarterly basis

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1. reports right now -→ fairly easy and straightforward
2. Mr. Antley

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1. solicited thoughts/suggestions from group about what the data layer will look

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1. like
   1. Mr. Sayers: when looking at data layer, we must ask visibility to whom? Carriers e.g., want to see stat plans eventually with more data. Can we put this in HDS per Mr.

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1. 1. Braswell's suggestion? Data layer could be an ephemeral pass-through that is part of the extraction pattern, or a standing entity where ETL transforms stat plan. Key questions: what are we asking the carriers to prove, and do they care about any format other than the stat plans?
   2. Mr. Antley: who are the voters in this RRDMWG? We have carriers, and we have regulators. Another critical question: if we just look at the easiest way to load this, and say, the carriers can just be done with loading the stat records, at this point who is tasked w/turning the stat records into a query that makes sense for the regulators? Without relying on regulators to expend the energy/effort into turning records into something useful?
   3. Mr. Sayers: There is discovery here. We start from the stat plan - may want to make it less codified to make it more workable, but it can be a perfectly viable raw material. We can throw some reports at it however and say how difficult is it to get from the stat plan data to this report?
   4. What are we asking carriers to provide and do they care about formats other than stat plans

Mr. Antley: carriers vs. regulators. For him, critical question: who is tasked with turning the stat records into a query that makes sense for regulators? 

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